A biometric is defined as a biological characteristic or trait that is unique to an individual and that can be accurately measured. A biometric that can be stored and accessed in an efficient manner can be used to identify an individual or to verify the identity of an individual. A biometric commonly used to identify human beings is one or more fingerprints belonging to the particular human being.
Fingerprint identification of a human being consists of two stages: enrollment and verification/identification. Enrollment of a fingerprint involves taking a fingerprint image (FPI) of an individual and storing the FPI itself or a plurality of data that is representative of the FPI in an FPI database. Identification of a fingerprint involves taking an FPI of an unknown individual and comparing the unknown FPI to the FPIs or FPI data that is stored in the FPI database. An identification is made when a match between the unknown FPI and an FPI stored in the FPI database is found that has a sufficient reliability that the probability of a false positive is below a predetermined threshold. Fingerprint verification or authentication matches an individual to a fingerprint that has been previously enrolled by that individual. Thus, identification involves searching for a match between a single unknown FPI with many stored FPIs. The verification process involves the matching an unknown or unconfirmed fingerprint minutiae template to a single previously enrolled fingerprint minutia template. Accordingly, the verification process is a one-to-one matching technique.
The use of biometrics to restrict access to secure entities such as computer networks, cryptographic keys, sensitive data, and physical locations is well known. In addition, smart cards, cards that have a biometric, such as a fingerprint, encoded thereon can be used to provide transaction security as well. A smart card allows a user to provide the biometric encoded on the card, wherein the encoded biometric data is compared to the biometric measured on the individual. In this way, a smartcard can positively authenticate the identity of the smartcard user.
However, traditional FPI data is based on the set of singularities that can be classified according the type of singularity, e.g., deltas, arches, or whorls. In addition, FPIs contain fingerprint minutiae that are the end point of a ridge curve or a bifurcation point of a ridge curve. FPI images can be classified and matched according to data associated with the fingerprint minutiae. This data can include the position of the minutiae, the tangential direction of the minutiae, and the distance to other minutiae. These types of FPI data can lead to a high false acceptance or identification rate when the unknown FPI has only a few minutiae or if the unknown FPI is only a partial FPI that may or may not include the number of minutiae needed to accurately verify or identify the unknown FPI.
Therefore what is needed is a method and apparatus to collect, analyze, and store FPI data such that an unknown or unverified FPI can be accurately verified or identified in the FPI or whether the FPI is only a partial print.